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From single drug targets to synergistic network pharmacology in ischemic stroke.

ABSTRACT: Drug discovery faces an efficacy crisis to which ineffective mainly single-target and symptom-based rather than mechanistic approaches have contributed. We here explore a mechanism-based disease definition for network pharmacology. Beginning with a primary causal target, we extend this to a second using guilt-by-association analysis. We then validate our prediction and explore synergy using both cellular in vitro and mouse in vivo models. As a disease model we chose ischemic stroke, one of the highest unmet medical need indications in medicine, and reactive oxygen species forming NADPH oxidase type 4 (Nox4) as a primary causal therapeutic target. For network analysis, we use classical protein-protein interactions but also metabolite-dependent interactions. Based on this protein-metabolite network, we conduct a gene ontology-based semantic similarity ranking to find suitable synergistic cotargets for network pharmacology. We identify the nitric oxide synthase (Nos1 to 3) gene family as the closest target to Nox4 Indeed, when combining a NOS and a NOX inhibitor at subthreshold concentrations, we observe pharmacological synergy as evidenced by reduced cell death, reduced infarct size, stabilized blood-brain barrier, reduced reoxygenation-induced leakage, and preserved neuromotor function, all in a supraadditive manner. Thus, protein-metabolite network analysis, for example guilt by association, can predict and pair synergistic mechanistic disease targets for systems medicine-driven network pharmacology. Such approaches may in the future reduce the risk of failure in single-target and symptom-based drug discovery and therapy.

SUBMITTER: Casas AI

PROVIDER: S-EPMC6452748 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

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From single drug targets to synergistic network pharmacology in ischemic stroke.

Casas Ana I AI Hassan Ahmed A AA Larsen Simon J SJ Gomez-Rangel Vanessa V Elbatreek Mahmoud M Kleikers Pamela W M PWM Guney Emre E Egea Javier J López Manuela G MG Baumbach Jan J Schmidt Harald H H W HHHW

Proceedings of the National Academy of Sciences of the United States of America 20190320 14

Drug discovery faces an efficacy crisis to which ineffective mainly single-target and symptom-based rather than mechanistic approaches have contributed. We here explore a mechanism-based disease definition for network pharmacology. Beginning with a primary causal target, we extend this to a second using guilt-by-association analysis. We then validate our prediction and explore synergy using both cellular in vitro and mouse in vivo models. As a disease model we chose ischemic stroke, one of the h ...[more]

PMID: 30894481

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Project description:Ischemic stroke (IS) is one of the major global causes of death and disability. Because blood clots block the neural arteries provoking ischemia and hypoxia in the brain tissue, IS results in irreversible neurological damage. Available IS treatments are currently limited. Curcumin has gained attention for many beneficial effects after IS, including neuroprotective and anti-inflammatory; however, its precise mechanism of action should be further explored. With network pharmacology, molecular docking, and molecular dynamics (MD), this study aimed to comprehensively and systematically investigate the potential targets and molecular mechanisms of curcumin on IS. We screened 1096 IS-related genes, 234 potential targets of curcumin, and 97 intersection targets. KEGG and GO enrichment analyses were performed on these intersecting targets. The findings showed that the treatment of IS using curcumin is via influencing 177 potential signaling pathways (AGE-RAGE signaling pathway, p53 signaling pathway, necroptosis, etc.) and numerous biological processes (the regulation of neuronal death, inflammatory response, etc.), and the AGE-RAGE signaling pathway had the largest degree of enrichment, indicating that it may be the core pathway. We also constructed a protein–protein interaction network and a component–target–pathway network using network pharmacology. From these, five key targets were screened: NFKB1, TP53, AKT1, STAT3, and TNF. To predict the binding conformation and intermolecular affinities of the key targets and compounds, molecular docking was used, whose results indicated that curcumin exhibited strong binding activity to the key targets. Moreover, 100 ns MD simulations further confirmed the docking findings and showed that the curcumin–protein complex could be in a stable state. In conclusion, curcumin affects multiple targets and pathways to inhibit various important pathogenic mechanisms of IS, including oxidative stress, neuronal death, and inflammatory responses. This study offers fresh perspectives on the transformation of curcumin to clinical settings and the development of IS therapeutic agents.

Project description:BackgroundIschemic stroke (IS) is a serious disease with a high rate of death and disability, and a growing number of people are becoming victims. Existing drugs not only have limited therapeutic effects but also have obvious side effects. Most importantly, drug resistance due to long-term or improper use of drugs is detrimental to patients. Therefore, it is urgent to find some alternative or supplementary medicines to alleviate the current embarrassment. Powerful Tianma Eucommia Capsule (PTEC) is mainly used to treat IS in China for thousands of years; however, the molecular mechanism is not clear.MethodsPharmacology ingredients and target genes were filtered and downloaded from websites. A pharmacology ingredient-target gene network was constructed to predict the molecular interactions between ingredients and target genes. Enrichment analysis was performed to explore the possible signal pathways. LeDock was used to simulate the interaction form between proteins and main active ingredients and to deduce key amino acid positions.ResultsTwo hundred eighty-nine target genes and seventy-four pharmacological ingredients were obtained from public databases. Several key ingredients (quercetin, kaempferol, and stigmasterol) and primary core target genes (PTGS1, NCOA2, and PRSS1) were detected through ingredient-target gene network analysis. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis demonstrated that ingredients affect networks mainly in nuclear receptor activity and G protein-coupled amine receptor activity; besides, fluid shear stress and atherosclerosis, human cytomegalovirus infection, and hepatitis B signaling pathways might be the principal therapy ways. A series of presumed key amino acid sites (189ASP, 190SER, 192GLN, 57HIS, and 99TYE) were calculated in PRSS1. Six of the target genes were differentially expressed between male and female patients.ConclusionsSeven new putative target genes (ACHE, ADRA1A, AR, CHRM3, F7, GABRA1, and PRSS1) were observed in this work. Based on the result of GO and KEGG analysis, this work will be helpful to further demonstrate the molecular mechanism of PTEC treatment of IS.

Project description:Buyang Huanwu Decoction (BYHWD) is used to promote blood circulation and is widely used in Chinese clinical practice for the treatment and prevention of ischemic cerebral vascular diseases. However, the mechanism and active compounds of BYHWD used to treat ischemic stroke are not well understood. The current study aimed to identify the potential active components of BYHWD and explore its mechanism using network pharmacology and bioinformatics analyses. The compounds of BYHWD were obtained from public databases. Oral bioavailability and drug-likeness were screened using the absorption, distribution, metabolism and excretion (ADME) criteria. Components of BYHWD, alongside the candidate targets of each component and the known therapeutic targets of ischemic stroke were collected. A network of target gene compounds and cerebral ischemia compounds was established using network pharmacology data sources. The enrichment of key targets and pathways was analyzed using STRING and DAVID databases. Moreover, three of key targets [IL6, VEGFA and hypoxia-inducible-factor-1α (HIF-1α)] were verified using western blot analysis. Network analysis determined 102 compounds in seven herbal medicines that were subjected to ADME screening. A total of 42 compounds as well as 79 genes formed the principal pathways associated with ischemic stroke. The 16 key compounds identified were baicalein, beta-carotene, baicalin, kaempferol, luteolin, quercetin, hydroxysafflor yellow A, isorhamnetin, bifendate, formononetin, calycosin, astragaloside IV, stigmasterol, sitosterol, Z-ligustilide, and dihydrocapsaicin. The core genes in this network were IL6, TNF, VEGFA, HIF-1α, MAPK1, MAPK3, JUN, STAT3, IL1B and IL10. Furthermore, the TNF, IL17, apoptosis, PI3K-Akt, toll-like receptor, MAPK, NF-κB and HIF-1 signaling pathways were identified to be associated with ischemic stroke. Compared with the control group (no treatment), BYHWD significantly inhibited the expression of IL6 and increase the expression of HIF-1α and VEGFA. Network pharmacology analyses can help to reveal close interactions between multi-components and multi-targets and enhance understanding of the potential effects of BYHWD on ischemic stroke.

Project description:Background: Osteosarcoma (OS) is a common primary tumor with extensive heterogeneity. In this study, we used single-cell RNA sequencing (scRNA-seq) and network pharmacology to analyze effective targets for Osteosarcoma treatment. Methods: The cell heterogeneity of the Osteosarcoma single-cell dataset GSE162454 was analyzed using the Seurat package. The bulk-RNA transcriptome dataset GSE36001 was downloaded and analyzed using the CIBERSORT algorithm. The key targets for OS therapy were determined using Pearson's correlation analysis. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed on key targets. The DeepDR algorithm was used to predict potential drugs for Osteosarcoma treatment. Molecular docking analysis was performed to verify the binding abilities of the predicted drugs and key targets. qRT-PCR assay was used to detect the expression of key targets in osteoblasts and OS cells. Results: A total of 21 cell clusters were obtained based on the GSE162454 dataset, which were labeled as eight cell types by marker gene tagging. Four cell types (B cells, cancer-associated fibroblasts (CAFs), endothelial cells, and plasmocytes) were identified in Osteosarcoma and normal tissues, based on differences in cell abundance. In total, 17 key targets were identified by Pearson's correlation analysis. GO and KEGG analysis showed that these 17 genes were associated with immune regulation pathways. Molecular docking analysis showed that RUNX2, OMD, and CD4 all bound well to vincristine, dexamethasone, and vinblastine. The expression of CD4, OMD, and JUN was decreased in Osteosarcoma cells compared with osteoblasts, whereas RUNX2 and COL9A3 expression was increased. Conclusion: We identified five key targets (CD4, RUNX2, OMD, COL9A3, and JUN) that are associated with Osteosarcoma progression. Vincristine, dexamethasone, and vinblastine may form a promising drug-target pair with RUNX2, OMD, and CD4 for Osteosarcoma treatment.

Project description:ObjectiveThe mechanism of action of Sanhua Decoction (SHD) in the treatment of ischemic stroke (IS) was analyzed based on the network pharmacology technology, and the pharmacodynamics and key targets were verified using the rat middle cerebral artery occlusion (MCAO) model.MethodsThe GEO database was used to collect IS-related gene set S D , and DrugBank and TTD databases were used to obtain the therapeutic drug target set S T . IS disease gene set S I was collected from DisGeNET, GeneCards, and OMIM databases. These three different gene sets obtained from various sources were merged, duplicates were removed, and the resulting IS disease gene set S IS was imported into the STRING database to establish the protein-protein interaction (PPI) network. Two methods were used to screen the key targets of IS disease based on the PPI network analysis. The TCMSP database and PubChem were applied to retrieve the main chemical components of SHD, and the ACD/Labs software and the SwissADME online system were utilized for ADMET screening. HitPick, SEA, and SwissTarget Prediction online systems were used to predict the set of potential targets for SHD to treat IS. The predicted set of potential targets and the IS disease gene set were intersected. Subsequently, the set of potential targets for SHD treatment of IS was identified, the target information was confirmed through the UniProt database, and finally, the component-target data set for SHD treatment of IS was obtained. clusterProfiler was used for GO function annotation and KEGG pathway enrichment analysis on the target set of SHD active ingredients. A rat MCAO model was established to evaluate the pharmacodynamics of SHD in the treatment of IS, and Western blot analysis assessed the level of proteins in the related pathways.ResultsThis study obtained 1,009 IS disease gene sets. PPI network analysis identified 12 key targets: AGT, SAA1, KNG1, APP, GNB3, C3, CXCR4, CXCL12, CXCL8, CXCL1, F2, and EDN1. Database analyses retrieved 40 active ingredients and 47 target genes in SHD. The network proximity algorithm was used to optimize the six key components in SHD. KEGG enrichment showed that the signaling pathways related to IS were endocrine resistance, estrogen, TNF signal pathway, and AGEs/RAGE. Compound-disease-target regulatory network analysis showed that AKT1, IL-6, TNF-α, TP53, VEGFA, and APP were related to the treatment of IS with SHD. Animal experiments demonstrated that SHD significantly reduces the neurological function of rat defect symptoms (P < 0.05), the area of cerebral avascular necrosis, and neuronal necrosis while increasing the levels of IL-6 and APP proteins (P < 0.05) and reducing the levels of AKT1 and VEGFA proteins (P < 0.05).ConclusionThe effective components of SHD may regulate multiple signaling pathways through IL-6, APP, AKT1, and VEGFA to reduce brain damage and inflammatory damage and exert a neuroprotective role in the treatment of IS diseases. Thus, this study provides a feasible method to study the pharmacological mechanism of traditional Chinese medicine compound prescriptions and a theoretical basis for the development of SHD into a new drug for IS treatment.

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From single drug targets to synergistic network pharmacology in ischemic stroke.

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From single drug targets to synergistic network pharmacology in ischemic stroke.

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